Single CpG Resolution Research Articles

Analysis and Visualization Tool for Targeted Amplicon Bisulfite Sequencing on Ion Torrent Sequencers.

Targeted sequencing of PCR amplicons generated from bisulfite deaminated DNA is a flexible, cost-effective way to study methylation of a sample at single CpG resolution and perform subsequent multi-target, multi-sample comparisons. Currently, no platform specific protocol, support, or analysis solution is provided to perform targeted bisulfite sequencing on a Personal Genome Machine (PGM). Here, we present a novel tool, called TABSAT, for analyzing targeted bisulfite sequencing data generated on Ion Torrent sequencers. The workflow starts with raw sequencing data, performs quality assessment, and uses a tailored version of Bismark to map the reads to a reference genome. The pipeline visualizes results as lollipop plots and is able to deduce specific methylation-patterns present in a sample. The obtained profiles are then summarized and compared between samples. In order to assess the performance of the targeted bisulfite sequencing workflow, 48 samples were used to generate 53 different Bisulfite-Sequencing PCR amplicons from each sample, resulting in 2,544 amplicon targets. We obtained a mean coverage of 282X using 1,196,822 aligned reads. Next, we compared the sequencing results of these targets to the methylation level of the corresponding sites on an Illumina 450k methylation chip. The calculated average Pearson correlation coefficient of 0.91 confirms the sequencing results with one of the industry-leading CpG methylation platforms and shows that targeted amplicon bisulfite sequencing provides an accurate and cost-efficient method for DNA methylation studies, e.g., to provide platform-independent confirmation of Illumina Infinium 450k methylation data. TABSAT offers a novel way to analyze data generated by Ion Torrent instruments and can also be used with data from the Illumina MiSeq platform. It can be easily accessed via the Platomics platform, which offers a web-based graphical user interface along with sample and parameter storage. TABSAT is freely available under a GNU General Public License version 3.0 (GPLv3) at https://github.com/tadkeys/tabsat/ and http://demo.platomics.com/.

Single-CpG resolution mapping of 5-hydroxymethylcytosine by chemical labeling and exonuclease digestion identifies evolutionarily unconserved CpGs as TET targets.

Conventional techniques for single-base resolution mapping of epigenetic modifications of DNA such as 5-hydroxymethylcytosine (5hmC) rely on the sequencing of bisulfite-modified DNA. Here we present an alternative approach called SCL-exo which combines selective chemical labeling (SCL) of 5hmC in genomic DNA with exonuclease (exo) digestion of the bead-trapped modified DNA molecules. Associated with a straightforward bioinformatic analysis, this new procedure provides an unbiased and fast method for mapping this epigenetic mark at high resolution. Implemented on mouse genomic DNA from in vitro-differentiated neural precursor cells, SCL-exo sheds light on an intrinsic lack of conservation of hydroxymethylated CpGs across vertebrates.Electronic supplementary materialThe online version of this article (doi:10.1186/s13059-016-0919-y) contains supplementary material, which is available to authorized users.

A full Bayesian partition model for identifying hypo- and hyper-methylated loci from single nucleotide resolution sequencing data.

BackgroudDNA methylation is an epigenetic modification that plays important roles on gene regulation. Study of whole-genome bisulfite sequencing and reduced representation bisulfite sequencing brings the availability of DNA methylation at single CpG resolution. The main interest of study on DNA methylation data is to test the methylation difference under two conditions of biological samples. However, the high cost and complexity of this sequencing experiment limits the number of biological replicates, which brings challenges to the development of statistical methods.ResultsBayesian modeling is well known to be able to borrow strength across the genome, and hence is a powerful tool for high-dimensional- low-sample- size data. In order to provide accurate identification of methylation loci, especially for low coverage data, we propose a full Bayesian partition model to detect differentially methylated loci under two conditions of scientific study. Since hypo-methylation and hyper-methylation have distinct biological implication, it is desirable to differentiate these two types of differential methylation. The advantage of our Bayesian model is that it can produce one-step output of each locus being either equal-, hypo- or hyper-methylated locus without further post-hoc analysis. An R package named as MethyBayes implementing the proposed full Bayesian partition model will be submitted to the bioconductor website upon publication of the manuscript.ConclusionsThe proposed full Bayesian partition model outperforms existing methods in terms of power while maintaining a low false discovery rate based on simulation studies and real data analysis including bioinformatics analysis.Electronic supplementary materialThe online version of this article (doi:10.1186/s12859-015-0850-3) contains supplementary material, which is available to authorized users.

MeSiC: A Model-Based Method for Estimating 5 mC Levels at Single-CpG Resolution from MeDIP-seq.

As the fifth base in mammalian genome, 5-methylcytosine (5 mC) is essential for many biological processes including normal development and disease. Methylated DNA immunoprecipitation sequencing (MeDIP-seq), which uses anti-5 mC antibodies to enrich for methylated fraction of the genome, is widely used to investigate methylome at a resolution of 100–500 bp. Considering the CpG density-dependent bias and limited resolution of MeDIP-seq, we developed a Random Forest Regression (RFR) model method, MeSiC, to estimate DNA methylation levels at single-base resolution. MeSiC integrated MeDIP-seq signals of CpG sites and their surrounding neighbors as well as genomic features to construct genomic element-dependent RFR models. In the H1 cell line, a high correlation was observed between MeSiC predictions and actual 5 mC levels. Meanwhile, MeSiC enabled to calibrate CpG density-dependent bias of MeDIP-seq signals. Importantly, we found that MeSiC models constructed in the H1 cell line could be used to accurately predict DNA methylation levels for other cell types. Comparisons with methylCRF and MEDIPS showed that MeSiC achieved comparable and even better performance. These demonstrate that MeSiC can provide accurate estimations of 5 mC levels at single-CpG resolution using MeDIP-seq data alone.

Epigenetic analysis of regulatory T cells using multiplex bisulfite sequencing.

This work was supported by Wellcome Trust Grant 096388, JDRF Grant 9-2011-253, the National Institute for Health Research Cambridge Biomedical Research Centre (BRC) and Award P01AI039671 (to LSW. and JAT.) from the National Institute of Allergy and Infectious Diseases (NIAID). CW is supported by the Wellcome Trust (089989). The content of this article is solely the responsibility of the authors and does not necessarily represent the official views of NIAID or the National Institutes of Health. The Cambridge Institute for Medical Research is in receipt of Wellcome Trust Strategic Award 100140. We gratefully acknowledge the participation of all NIHR Cambridge BioResource volunteers. We thank the Cambridge BioResource staff for their help with volunteer recruitment. We thank members of the Cambridge BioResource SAB and Management Committee for their support of our study and the National Institute for Health Research Cambridge Biomedical Research Centre for funding. We thank Fay Rodger and Ruth Littleboy for running the Illumina MiSeq in the Molecular Genetics Laboratories, Addenbrooke's Hospital, Cambridge. This research was supported by the Cambridge NIHR BRC Cell Phenotyping Hub. In particular, we wish to thank Anna Petrunkina Harrison, Simon McCallum, Christopher Bowman, Natalia Savinykh, Esther Perez and Jelena Markovic Djuric for their advice and support in cell sorting. We also thank Helen Stevens, Pamela Clarke, Gillian Coleman, Sarah Dawson, Jennifer Denesha, Simon Duley, Meeta Maisuria-Armer and Trupti Mistry for acquisition and preparation of samples.

An improved sequencing-based strategy to estimate locus-specific DNA methylation

BackgroundDNA methylation is an important epigenetic mechanism of transcriptional control that plays an essential role in several cellular functions. Aberrant DNA methylation in cancer has been frequently associated with downregulation of microRNAs and protein coding genes, such as miR-200c/miR-141 cluster and E-cadherin. Current strategies to assess DNA methylation, including bisulfite treatment-based assays, tend to be time-consuming and may be quite expensive when a precise appraisal is required. The Sanger-sequencing of the amplified bisulfite-treated DNA (BSP) might represent a practical option to measure DNA methylation at single CpG resolution. However, this strategy often produces noisy data, which affects accurate quantification. Here we propose an improved, reliable and cost-effective BSP-based protocol that allows proper DNA methylation assessment.MethodsOur strategy, named normalized-BSP (NBSP), takes advantage of tailed C-balanced primers and a normalization procedure based on C/T ratio to overcome BSP-associated noise problems and nucleotide signal unbalance. NBSP was applied to estimate miR-200c/miR-141 locus methylation in serial dilution experiments and was compared to conventional methods. Besides, it was applied in the analysis of FFPE breast cancer samples and further validated in the context of the E-cadherin promoter.ResultsNBSP strategy outperformed conventional BSP in the estimate of the fraction of methylated cytosine in serial dilution experiments, providing data in agreement with the widely used but cumbersome cloning-based protocol. This held true for both miR-200c/miR-141 locus and E-cadherin promoter analyses. Moreover, the miR-200c/miR-141 locus methylation reflected the decrease in miRNA expression both in breast cancer cell lines and in the FFPE samples.ConclusionsNBSP is a rapid and economical method to estimate the extent of methylation at each CpG of a given locus. Notably, NBSP works efficiently on FFPE samples, thus disclosing the perspective of its application also in the diagnostic setting.Electronic supplementary materialThe online version of this article (doi:10.1186/s12885-015-1646-6) contains supplementary material, which is available to authorized users.

MP58-03 IDENTIFICATION OF SPECIFIC METHYLATION-BASED BIOMARKERS FOR THE ASSESSMENT OF THE METASTATIC RISK OF MUSCLE INVASIVE BLADDER CANCER

You have accessJournal of UrologyBladder Cancer: Invasive II1 Apr 2015MP58-03 IDENTIFICATION OF SPECIFIC METHYLATION-BASED BIOMARKERS FOR THE ASSESSMENT OF THE METASTATIC RISK OF MUSCLE INVASIVE BLADDER CANCER Beatrice Stubendorff, Kerstin Wilhelm, Kathleen Posselt, James Catto, Elke Schaeffeler, Matthias Schwab, Arndt Hartmann, Susanne Füssel, Vladimir Novotny, Mieczyslaw Gajda, Marc-Oliver Grimm, Michael Stöckle, and Kerstin Junker Beatrice StubendorffBeatrice Stubendorff More articles by this author , Kerstin WilhelmKerstin Wilhelm More articles by this author , Kathleen PosseltKathleen Posselt More articles by this author , James CattoJames Catto More articles by this author , Elke SchaeffelerElke Schaeffeler More articles by this author , Matthias SchwabMatthias Schwab More articles by this author , Arndt HartmannArndt Hartmann More articles by this author , Susanne FüsselSusanne Füssel More articles by this author , Vladimir NovotnyVladimir Novotny More articles by this author , Mieczyslaw GajdaMieczyslaw Gajda More articles by this author , Marc-Oliver GrimmMarc-Oliver Grimm More articles by this author , Michael StöckleMichael Stöckle More articles by this author , and Kerstin JunkerKerstin Junker More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2015.02.2142AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES Adjuvant chemotherapy improves the outcome of bladder cancer patients at risk for the development of metastases. However, there are no parameters available that allow an individual risk assessment. The aim of this project is to identify a specific DNA methylation pattern that provides a reliable tool for prognosis assessment of muscle invasive bladder tumors and to understand metastasis associated processes regulated by DNA methylation. METHODS we validated differentially methylated genes in two independent cohorts of primary bladder tumors (n=91). Candidate promoter methylation and gene expression were assessed by quantitative analysis of DNA methylation using real-time PCR and qRT-PCR. Quantitative CpG specific methylation level of KISS1R was performed with MALDI-TOF-MS and analyzed using Epityper 1.0 software. Protein expression was determined by immunohistochemical analysis for KISS1R on tissue microarrays from 2 independent patient cohorts comprising 291 muscle-invasive bladder carcinomas. For analyzing the gene function in tumor cell behavior, bladder cancer cells were transfected with siRNA or cDNA clones. Changes in proliferation and migration were measured using real-time cell monitoring. Invasion assay was performed using matrigel coated cell culture inserts. RESULTS Methylation differences were confirmed for KISS1R, SEPT9 (p=0.002) and CSAD (p=0.01). MALDI-TOF analysis provided a tool to validate the DNA methylation at single CpG resolution. The combination of the three genes predicted the metastatic risk of the primary tumors with sensitivity of 90% and specificity of 67% in patient cohort 1 and sensitivity of 75% and specificity of 70% in patient cohort 2. Protein expression of KISS1R was significantly reduced in correlation to positive lymph nodes (p<0.001). Knock down of SEPT9v3 resulted in increased cell migration by 28% (p=0.04) and increased invasion by 22% (p=0.004). Overexpression of KISS1R resulted in decreased cell migration (25%, p=0.1). CONCLUSIONS Muscle-invasive bladder tumors show significant differences in the DNA methylation pattern in correlation to the metastatic potential. KISS1R is characterized by strongest association with the metastatic risk of primary tumors on methylation. Reduced expression of KISS1R and SEPT9 regulated by DNA methylation seems to be involved in metastasis-associated processes. The combination of candidate genes KISS1R, CSAD and SEPT9 could serve as prognostic marker panel for determination of the metastatic risk of primary bladder tumors. © 2015 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 193Issue 4SApril 2015Page: e722 Advertisement Copyright & Permissions© 2015 by American Urological Association Education and Research, Inc.MetricsAuthor Information Beatrice Stubendorff More articles by this author Kerstin Wilhelm More articles by this author Kathleen Posselt More articles by this author James Catto More articles by this author Elke Schaeffeler More articles by this author Matthias Schwab More articles by this author Arndt Hartmann More articles by this author Susanne Füssel More articles by this author Vladimir Novotny More articles by this author Mieczyslaw Gajda More articles by this author Marc-Oliver Grimm More articles by this author Michael Stöckle More articles by this author Kerstin Junker More articles by this author Expand All Advertisement Advertisement PDF downloadLoading ...

Inter-locus as well as intra-locus heterogeneity in LINE-1 promoter methylation in common human cancers suggests selective demethylation pressure at specific CpGs

BackgroundHypomethylation of long interspersed element (LINE)-1 has been observed in tumorigenesis when using degenerate assays, which provide an average across all repeats. However, it is unknown whether individual LINE-1 loci or different CpGs within one specific LINE-1 promoter are equally affected by methylation changes. Conceivably, studying methylation changes at specific LINE-1 may be more informative than global assays for cancer diagnostics. Therefore, with the aim of mapping methylation at individual LINE-1 loci at single-CpG resolution and exploring the diagnostic potential of individual LINE-1 locus methylation, we analyzed methylation at 11 loci by pyrosequencing, next-generation bisulfite sequencing as well as global LINE-1 methylation in bladder, colon, pancreas, prostate, and stomach cancers compared to paired normal tissues and in blood samples from some of the patients compared to healthy donors.ResultsMost (72/80) tumor samples harbored significant methylation changes at at least one locus. Notably, our data revealed not only the expected hypomethylation but also hypermethylation at some loci. Specific CpGs within the LINE-1 consensus sequence appeared preferentially hypomethylated suggesting that these could act as seeds for hypomethylation. In silico analysis revealed that these CpG sites more likely faced the histones in the nucleosome. Multivariate logistic regression analysis did not reveal a significant clinical advantage of locus-specific methylation markers over global methylation markers in distinguishing tumors from normal tissues.ConclusionsMethylation changes at individual LINE-1 loci are heterogeneous, whereas specific CpGs within the consensus sequence appear to be more prone to hypomethylation. With a broader selection of loci, locus-specific LINE-1 methylation could become a tool for tumor detection.Electronic supplementary materialThe online version of this article (doi:10.1186/s13148-015-0051-y) contains supplementary material, which is available to authorized users.

Quantitative DNA Methylation Analysis by Pyrosequencing®.

DNA methylation is an epigenetic mark playing an important role in development and disease. Aberrant DNA methylation was identified as an alternative mechanism for gene inactivation complementing deletions and mutations in cancer initiation and progression. However, to accurately compare differences in DNA methylation among various tissue types, adequate quantitative approaches are required. Pyrosequencing(®), as a sequencing-by-synthesis method, allows such quantification with single CpG resolution and the ability for threshold determination. This book chapter provides a detailed protocol for DNA methylation analysis by Pyrosequencing, including information on assay design and practical procedure. Additionally, emphasis is placed on the discussion of strengths and weaknesses of the methodology.

Abstract 374: A novel sequencing method for genome-wide profiling of 5-hydroxymethylcytosine with single-base resolution

Abstract 5-hydroxymethylcytosine (5hmC) is an epigenetic mark abundant in embryo stem cells and brain tissues. The exact biological functions of 5hmC are still under close investigation although several lines of evidence have indicated it could be involved in active DNA demethylation. Meanwhile, extensive studies have been carried out to determine its genomic distribution. A number of approaches have been developed using either affinity based enrichment, such as hMeDIP, that rely on antibody and other specific binding proteins to target 5hmC, or modified bisulfite sequencing, namely oxidative bisulfite sequencing (OxBS) and TET assisted bisulfite sequencing (TAB-sequencing). However, all those methods have limitations which hamper their application. For example, affinity based methods lack single base resolution while modified bisulfite sequencing methods require efficient chemical or enzymatic oxidation which cannot be easily achieved or guaranteed. As an alternative, we have developed a novel genome-wide sequencing method that utilizes an enzyme based modification approach coupled with bisulfite-sequencing for detecting 5hmC. This methodology allows quantification of 5hmC levels with single CpG resolution and can also be employed for locus-specific assays. Using this method, we were able to map and quantify 5hmC sites at the genomic scale for several different biological samples. This novel method can determine the exact location and abundance of 5hmC, which will facilitate our understanding of 5hmC in regulating gene expression in different biological contexts. Citation Format: Xueguang Sun, Tzu-Hung Chung, Yap Ching Chew, Darany Tan, Xi-Yu Jia. A novel sequencing method for genome-wide profiling of 5-hydroxymethylcytosine with single-base resolution. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 374. doi:10.1158/1538-7445.AM2014-374

Abstract 1370: Epigenetic clustering of gastric carcinoma based on DNA methylation profiles at the precancerous stage: its correlation with tumor aggressiveness and patient outcome

Abstract Aim: The aim of this study was to clarify the significance of DNA methylation alterations during gastric carcinogenesis. Background: DNA methylation alterations are induced by carcinogenetic factors at the precancerous stage in various organs. As for gastric mucosae, aberrant DNA methylation is considered to be induced by Helicobacter pylori, Epstein-Barr virus and other carcinogenetic factors. Since field cancerization concept has become evident in the stomach, non-cancerous gastric mucosae obtained from patients with gastric carcinomas (GCs) can be at the precancerous stage. However, correlations between DNA methylation profiles in such non-cancerous gastric mucosae at the precancerous stage and clinicopathological aggressiveness of GCs developing in the individual same patients and patient outcome have not been clarified. Methods: Single-CpG resolution genome-wide DNA methylation analysis using the Infinium HumanMethylation27 Bead Array (Illumina) was performed in 110 paired samples of non-cancerous gastric mucosa (N) and tumorous tissue (T) from patients with GCs. Results: DNA methylation alterations on 3,877 probes occurred in T samples relative to N samples. Since Ns can be at the precancerous stage according to field cancerization concept, we first focused on DNA methylation levels in N samples (βN) and performed unsupervised hierarchical clustering using βN on the 3,877 probes. 110 patients with GCs were subclustered into Cluster A (n=20), Cluster B1 (n=20) and Cluster B2 (n=70). GCs belonging to Cluster B1 more frequently showed undifferentiated histology and higher pT stage and pathological TNM stage when compared to those in Clusters A and B2. Recurrence-free and overall survival rates of patients in Cluster B1 were lower than those of patients in Clusters A and B2. Sixty hallmark genes of which βN characterized the epigenetic clustering were identified. To examine whether DNA methylation profiles in N samples were inherited by GCs themselves, we next focused on DNA methylation levels of the 60 hallmark genes in T samples (βT). In 43 out of the 60 hallmark genes, βT was again significantly correlated with undifferentiated histology or higher pT stage and pathological TNM stage. In 25 and 26 out of the 60 hallmark genes, βT was significantly correlated with recurrence-free and overall survival rates of the 110 patients, respectively. Multivariate analyses using Cox proportional hazards regression model revealed that βT in 10 out of the 60 hallmark genes were a significant prognostic factor which was independent from histological differentiation, pT stage and pathological TNM stage. Conclusion: These data indicated that DNA methylation profiles at the precancerous stage may be inherited by GCs themselves and may determine tumor aggressiveness and patient outcome. Citation Format: Kazuhiro Yamanoi, Eri Arai, Yoriko Takahashi, Sayaka Miyata, Ryoji Kushima, Hitoshi Katai, Michiie Sakamoto, Yae Kanai. Epigenetic clustering of gastric carcinoma based on DNA methylation profiles at the precancerous stage: its correlation with tumor aggressiveness and patient outcome. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 1370. doi:10.1158/1538-7445.AM2014-1370

Abstract 391: Identification of a novel tumor-suppressor gene through methylome analysis in smoking-associated lung adenocarcinoma

Abstract Aberrant methylation of promoter DNA and transcriptional repression of specific tumor suppressor genes (TSGs) play an important role in carcinogenesis. In order to identify novel TSG candidates implicated in smoking-associated lung adenocarcinoma (AC), we performed genome-wide methylation profiling of six smoking-associated lung ACs with paired non-cancerous tissues using the single-CpG resolution Infinium array. After defining differentially methylated candidates including known targets in ACs, we analyzed gene expression using microarray/RT-PCR to identify genes potentially silenced by promoter methylation. Frequent hypermethylation and downregulation of candidates was further validated by pyrosequencing and RT-PCR/immunohistochemistry, respectively, in a larger set of ACs, and methylation dependency of silencing was determined by 5-aza-2-deoxycytidine treatment and promoter assay in AC cell lines. Through this approach, we identified one gene matching all of our selection criteria for a possible TSG (HSLAC1, Lab. name). Additionally, functional analyses supported a tumor-suppressive activity in vitro. Our results implicate HSLAC1 as a novel TSG for smoking-associated lung AC. Citation Format: Issei Imoto. Identification of a novel tumor-suppressor gene through methylome analysis in smoking-associated lung adenocarcinoma. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 391. doi:10.1158/1538-7445.AM2014-391

Modeling DNA methylation dynamics with approaches from phylogenetics.

Motivation: Methylation of CpG dinucleotides is a prevalent epigenetic modification that is required for proper development in vertebrates. Genome-wide DNA methylation assays have become increasingly common, and this has enabled characterization of DNA methylation in distinct stages across differentiating cellular lineages. Changes in CpG methylation are essential to cellular differentiation; however, current methods for modeling methylation dynamics do not account for the dependency structure between precursor and dependent cell types.Results: We developed a continuous-time Markov chain approach, based on the observation that changes in methylation state over tissue differentiation can be modeled similarly to DNA nucleotide changes over evolutionary time. This model explicitly takes precursor to descendant relationships into account and enables inference of CpG methylation dynamics. To illustrate our method, we analyzed a high-resolution methylation map of the differentiation of mouse stem cells into several blood cell types. Our model can successfully infer unobserved CpG methylation states from observations at the same sites in related cell types (90% correct), and this approach more accurately reconstructs missing data than imputation based on neighboring CpGs (84% correct). Additionally, the single CpG resolution of our methylation dynamics estimates enabled us to show that DNA sequence context of CpG sites is informative about methylation dynamics across tissue differentiation. Finally, we identified genomic regions with clusters of highly dynamic CpGs and present a likely functional example. Our work establishes a framework for inference and modeling that is well suited to DNA methylation data, and our success suggests that other methods for analyzing DNA nucleotide substitutions will also translate to the modeling of epigenetic phenomena.Availability and implementation: Source code is available at www.kostkalab.net/software.Contact: tony.capra@vanderbilt.edu or kostka@pitt.edu

Whole-genome bisulfite sequencing of HSCs and their immediate progeny identifies novel regulatory elements involved in self-renewal and early hematopoietic commitment

Hematopoietic stem cells (HSC) are capable of life-long self-renewal and multi-lineage differentiation and their commitment involves epigenetic remodeling. However, a comprehensive genome-wide map detailing epigenetically regulated elements is lacking since classic whole-genome bisulfite sequencing (WGBS) requires μg amounts of DNA. Recently, tagmentation-based WGBS (TWGBS) was developed and works reliably with 10-30 ng DNA. We applied TWGBS on HSC (LSK/CD34-/CD48-/CD150+) and their immediate progeny (MPP1 [LSK/CD34+/CD48-/CD150+], MPP2 [LSK/CD34+/CD48+/CD150+], and MPP3/4 [LSK/CD34+/CD48+/CD150-]) and generated genome-wide single CpG resolution methylation maps.

DNA Sequence Explains Seemingly Disordered Methylation Levels in Partially Methylated Domains of Mammalian Genomes

For the most part metazoan genomes are highly methylated and harbor only small regions with low or absent methylation. In contrast, partially methylated domains (PMDs), recently discovered in a variety of cell lines and tissues, do not fit this paradigm as they show partial methylation for large portions (20%–40%) of the genome. While in PMDs methylation levels are reduced on average, we found that at single CpG resolution, they show extensive variability along the genome outside of CpG islands and DNase I hypersensitive sites (DHS). Methylation levels range from 0% to 100% in a roughly uniform fashion with only little similarity between neighboring CpGs. A comparison of various PMD-containing methylomes showed that these seemingly disordered states of methylation are strongly conserved across cell types for virtually every PMD. Comparative sequence analysis suggests that DNA sequence is a major determinant of these methylation states. This is further substantiated by a purely sequence based model which can predict 31% (R2) of the variation in methylation. The model revealed CpG density as the main driving feature promoting methylation, opposite to what has been shown for CpG islands, followed by various dinucleotides immediately flanking the CpG and a minor contribution from sequence preferences reflecting nucleosome positioning. Taken together we provide a reinterpretation for the nucleotide-specific methylation levels observed in PMDs, demonstrate their conservation across tissues and suggest that they are mainly determined by specific DNA sequence features.

EMethylsorb: electrochemical quantification of DNA methylation at CpG resolution using DNA-gold affinity interactions.

We report a simple electrochemical method referred to as "eMethylsorb" for the detection of DNA methylation. The method relies on the base dependent affinity interaction of DNA with gold. The methylation status of DNA is quantified by monitoring the electrochemical current as a function of the relative adsorption level of bisulphite treated DNA samples onto a bare gold electrode. This method can successfully distinguish methylated and unmethylated epigenotypes at single CpG resolution.

MOABS: model based analysis of bisulfite sequencing data

Bisulfite sequencing (BS-seq) is the gold standard for studying genome-wide DNA methylation. We developed MOABS to increase the speed, accuracy, statistical power and biological relevance of BS-seq data analysis. MOABS detects differential methylation with 10-fold coverage at single-CpG resolution based on a Beta-Binomial hierarchical model and is capable of processing two billion reads in 24 CPU hours. Here, using simulated and real BS-seq data, we demonstrate that MOABS outperforms other leading algorithms, such as Fisher’s exact test and BSmooth. Furthermore, MOABS analysis can be easily extended to differential 5hmC analysis using RRBS and oxBS-seq. MOABS is available at http://code.google.com/p/moabs/.

Epigenomic Evolution In Diffuse Large B-Cell Lymphomas

Diffuse Large B-cell Lymphoma (DLBCL) is the most common non-Hodgkin lymphoma worldwide. It is a heterogeneous disease in which one third of patients either do not respond to treatment or relapse within five years after chemotherapy. It is unclear whether epigenetic alterations are responsible for B cell lymphomas relapse phenotypes, such as increased aggressiveness and chemoresistance. To investigate how the B cell lymphoma epigenome evolves upon chemotherapy, we used Enhanced Reduced Representation Bisulfite Sequencing (ERRBS) to profile DNA methylation genome-wide in primary matched diagnosis-relapse DLBCL samples.We interrogated 13 pairs of DLBCL diagnosis tumors and their matched relapse samples. In addition, we performed methylation profiling of normal tonsilar B cell subsets (Naïve and germinal center B cells) from two healthy human individuals. ERRBS provided DNA methylation levels at 3-4M CpG sites. When combining methylation levels from all interrogated CpG sites, we observed increased DNA methylation levels at CpG-islands (CGIs; p=3.5e-9, t-test) in DLBCLs compared to normal B cells, and stable or slightly decreasing methylation levels outside of CGIs (>10 kb away from known CGIs; p=0.057, t-test). There was no significant change in average DNA methylation levels from diagnosis to relapse either at CGIs or outside of CGIs. However, when we investigated DNA methylation changes at gene promoters, we identified 107 consistently differentially methylated promoters between diagnosis and relapse (> 10% DNA methylation alteration and p < 0.05, paired t-test). Pathway analysis of the corresponding genes using iPAGE identified several pathways and processes associated with either hyper or hypo-methylated genes in relapse, demonstrating that methylation changes associated with relapse are functionally coherent. For example, several genes with TGF-beta receptor activity displayed lower DNA methylation in relapse.Taking advantage of single CpG resolution and high coverage provided by ERRBS, we then sought to investigate the extent of allele-specific methylation (ASM) levels in normal tissues and DLBCL patients. We found increased ASM levels in DLBCLs compared to normal tissues (p=0.0011, t-test) confirming observations in solid tumors. There was no significant change in ASM levels from diagnosis to relapse (p=0.24, t-test). These results suggest that methylation changes associated with lymphomagenesis might frequently involve one allele only, perhaps due to differential nuclear localization of individual chromosomes. However allele-specific methylation may not play a key role in lymphoma progression.Finally, we investigated whether intra-tumor methylation heterogeneity at diagnosis would predict whether a DLBCL patient would relapse. We quantified intra-tumor methylation heterogeneity using a statistical approach based on the probability that two randomly sampled DNA molecules from the tumor cell populations differ from each other in their methylation pattern. We found decreased intra-sample methylation heterogeneity in DLBCLs compared to normal germinal center B cells (p=1.9e-4, t-test), consistent with the clonal origin of tumors. 12 out of 13 pairs also displayed decreased methylation heterogeneity from diagnosis to relapse, which is also consistent with clonal selection upon chemotherapy treatment. We then performed ERRBS on primary tumors from 8 DLBCL patients who have not relapsed five years after treatment. We found that non-relapse patients displayed significantly lower intra-tumor methylation heterogeneity as compared to that of the relapsed patients (p=0.047, t-test), which suggests that increased epigenetic diversity within a population of tumor cells at diagnosis might fuel the Darwinian evolutionary process underlying relapse. We also looked at genetic clonal heterogeneity based on next-generation sequencing of somatic hypermutation profiles in IGH VDJ sequences, but found no differences between relapsed and not relapsed patients (p=0.22, Wilcoxon test). This suggests that epigenetic heterogeneity plays a more substantial role than clonal heterogeneity in fueling the relapse phenotype.In summary, this study provides the first comprehensive characterization of aberrations in DNA methylation in relapse DLBCLs and identified epigenetic diversity in DLBCLs as a potential predictor of relapse. Disclosures:No relevant conflicts of interest to declare.

Estimating absolute methylation levels at single-CpG resolution from methylation enrichment and restriction enzyme sequencing methods

Recent advancements in sequencing-based DNA methylation profiling methods provide an unprecedented opportunity to map complete DNA methylomes. These include whole-genome bisulfite sequencing (WGBS, MethylC-seq, or BS-seq), reduced-representation bisulfite sequencing (RRBS), and enrichment-based methods such as MeDIP-seq, MBD-seq, and MRE-seq. These methods yield largely comparable results but differ significantly in extent of genomic CpG coverage, resolution, quantitative accuracy, and cost, at least while using current algorithms to interrogate the data. None of these existing methods provides single-CpG resolution, comprehensive genome-wide coverage, and cost feasibility for a typical laboratory. We introduce methylCRF, a novel conditional random fields–based algorithm that integrates methylated DNA immunoprecipitation (MeDIP-seq) and methylation-sensitive restriction enzyme (MRE-seq) sequencing data to predict DNA methylation levels at single-CpG resolution. Our method is a combined computational and experimental strategy to produce DNA methylomes of all 28 million CpGs in the human genome for a fraction (<10%) of the cost of whole-genome bisulfite sequencing methods. methylCRF was benchmarked for accuracy against Infinium arrays, RRBS, WGBS sequencing, and locus-specific bisulfite sequencing performed on the same human embryonic stem cell line. methylCRF transformation of MeDIP-seq/MRE-seq was equivalent to a biological replicate of WGBS in quantification, coverage, and resolution. We used conventional bisulfite conversion, PCR, cloning, and sequencing to validate loci where our predictions do not agree with whole-genome bisulfite data, and in 11 out of 12 cases, methylCRF predictions of methylation level agree better with validated results than does whole-genome bisulfite sequencing. Therefore, methylCRF transformation of MeDIP-seq/MRE-seq data provides an accurate, inexpensive, and widely accessible strategy to create full DNA methylomes.

Abstract 5364: DNA methylation profiles at precancerous stage cluster lung adenocarcinomas into subclusters associated with carcinogenetic pathway, clinicopathological aggressiveness and patient outcome.

Abstract Background: We have reported DNA methylation alterations in non-cancerous lung tissue obtained from lung cancer patients. These previous data drew our attention to DNA methylation alterations at precancerous stage of lung adenocarcinoma (LADC). However, the impact of DNA methylation alterations at precancerous stage on the characteristics of established LADCs has been unclear. The purpose of this study is to clarify the significance of DNA methylation profiles during lung carcinogenesis. Methods: Using single-CpG resolution Infinium array, genome-wide DNA methylation analysis was performed in 36 samples of normal lung tissue (C), 139 samples of non-cancerous lung tissue (N) obtained from patients with LADCs, and the corresponding 139 samples of tumorous tissue (T) as a learning cohort. As a validation cohort, the 50 paired samples of N and the corresponding T were obtained from patients with primary LADCs. Results: 3,621 probes showed significant differences in DNA methylation levels between the 36 C and 139 N samples in the learning cohort, suggesting that N was at precancerous stage with DNA methylation alterations. Unsupervised hierarchical clustering using DNA methylation levels of N on 26,447 autosomal probes subclustered 139 patients of the learning cohort into Cluster A (n=32), B (n=35) and C (n=72). Most of patients in Cluster A were heavy smokers and frequently showed severe pleural anthracosis which mainly reflects smoking history. LADCs in Cluster A were locally invasive tumors which develop in emphysematous lung tissue associated with inflammation. Most of patients in Cluster B were non-smokers and LADCs in Cluster B showed less aggressive features. Most of patients in Cluster C were light smokers and LADCs in Cluster C showed more frequent lymph node metastasis and higher Tumor-Node-Metastasis (TNM) stages. The cancer-free and overall survival rates of patients in Cluster C were significantly lower than those of Cluster B. We indetified 21, 26 and 35 probes as markers which characterize Clusters A, B and C, respectively. In the validation cohort, DNA methylation levels of Cluster A, B and C marker probes were significantly correlated with pleural anthracosis, never-smoking history, and lymph node metastases and higher TNM stages, respectively, i.e. correlation between DNA methylation profiles and each clinicopathological parameter were validated in the validation cohort. Conclusion: DNA methylation profiles of Clusters A and C at precancerous stage may be established by the effects of smoking through or not thorough inflammation, respectively, whereas those of Cluster B may be associated with carcinogenesis in non-smokers. DNA methylation profiles at precancerous stage may underlie distinct pathways of lung carcinogenesis and determine tumor aggressiveness and patient outcome. Citation Format: Takashi Sato, Eri Arai, Takashi Kohno, Koji Tsuta, Shun-ichi Watanabe, Kenzo Soejima, Tomoko Betsuyaku, Yae Kanai. DNA methylation profiles at precancerous stage cluster lung adenocarcinomas into subclusters associated with carcinogenetic pathway, clinicopathological aggressiveness and patient outcome. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 5364. doi:10.1158/1538-7445.AM2013-5364